Stage 4 · Mastery I — Quantitative Trader · ₹14,999
Stage 4: turn the documented playbook into code, with statistical integrity.
Stage 3's playbook is judgment-driven application of documented rules. Stage 4 turns those rules into Python — backtested with statistical integrity, regime-conditioned, factor-decomposed, and stress-tested via Monte Carlo. The transition from discretionary to systematic isn't about removing judgment; it's about isolating the parts that can be coded from the parts that can't.
The five Stage 4 volumes
The minimum viable Python toolkit
Pandas for time-series. Numpy for vector math. Matplotlib for visual diagnostics. Scikit-learn for regression and classification. Statsmodels for cointegration and stationarity tests. The volume assumes no prior Python; by the end of it, you can read OHLCV data into a DataFrame, compute technical indicators from scratch, and visualise a strategy's equity curve. Includes 12 Jupyter notebooks — each ~80 lines — that you run and modify directly.
Why most retail backtests are useless
Look-ahead bias. Survivorship bias. Data-snooping bias. In-sample vs out-of-sample distinction. Walk-forward analysis. The four backtest results that look good but mean nothing. Includes the Sharpe ratio's blind spots, why max drawdown matters more than CAGR for retail, and the Lopez de Prado sequential-bootstrap test for assessing whether observed edge is statistically distinguishable from luck.
Decomposing returns into components you understand
Why a strategy's return is not one number but a decomposition: market beta + factor exposures + idiosyncratic alpha. The four canonical factors (size, value, momentum, quality) and how to compute factor exposures from a backtest. Regime-conditional factor analysis: which factors are paying in which regime. Includes the Indian-market specifics — Nifty 50 has materially different factor structure from S&P 500.
Stress-test the system before live capital touches it
Trade-sequence randomisation: take the trade-by-trade R-multiple distribution from your backtest and resample 10,000 times to produce a drawdown distribution. The expected vs worst-case drawdown gap. Risk-of-ruin computation conditional on percent-risk-per-trade and edge strength. Sequence dependency — why the same expectancy in different orders produces different account paths. The simulator is a Python notebook; you run it on your own backtest output.
Build, backtest, paper-trade, and grade your own systematic translation of one Stage 3 setup
Eight-week supervised exercise. Pick one setup from your Stage 3 playbook. Translate it into Python. Backtest with walk-forward integrity. Validate with Monte Carlo. Paper-trade for two weeks. Submit code + journal for grading. Pass = automatic Stage 5 discount code. Fail = re-grade with detailed feedback; lifetime access means no penalty for re-takes. Most students pass on first attempt; some require a second pass to address backtest-integrity issues.
What Stage 4 is not
- Not a Python bootcamp. It's a systematic-trading curriculum that uses Python as the implementation language. We assume zero Python; we don't aim to produce software engineers.
- Not a full algorithmic trading framework. Stage 4 builds the analytical foundation; Stage 5 (Systems Architect) builds the execution architecture.
- Not a substitute for trading judgment. The systematic translation isolates the codeable parts and preserves the parts that aren't. Most edge in retail trading lives in the regime-classification and risk-overlay layers, which remain human-led at Stage 4.
Who should buy Stage 4 right now
- You completed Stage 3 capstone. Your 25-setup playbook has been running for at least 4 weeks. You're ready to translate the most stable setup into code.
- You want backtesting integrity. Most retail backtest claims you've seen are statistically wrong. Stage 4 fixes that gap.
- You want to understand why a strategy works, not just that it works. The factor decomposition + Monte Carlo workflow is the institutional answer.
- You have any aspiration toward AIF Cat III, fund management, or a SEBI-RA practice. Stage 4 is the analytical floor for those careers.
Who should NOT buy Stage 4 yet
- You haven't passed Stage 3 capstone. The systematic translation requires a documented setup to translate — without that, Stage 4 has no inputs.
- You want a black-box trading system delivered. Stage 4 builds your system using your inputs; we don't sell pre-made strategies.
- You're allergic to code. The 12 notebooks are not optional. We try to make Python accessible; we can't make it unnecessary.
Enrol in Stage 4
₹14,999 all-inclusive · 5 volumes · 12 Python notebooks · 8-week capstone · Lifetime access · 7-day refund window.
Enrol Stage 4 — ₹14,999Bharath Shiksha is an educational publisher. We do not provide investment advice. The curriculum uses anonymised historical examples with at least 30-day data lag; no specific securities are named for buy/sell/hold; no performance claims, return projections, or accuracy statistics are made. Trading involves substantial risk of capital loss.